Trends and factors associated with teenage pregnancy in Ethiopia: multivariate decomposition analysis

Teenage is a time of transition from childhood to adulthood. This stage is a time of change and needs particular care and ongoing support. Adolescent pregnancy remains a common health care problem in low- and middle-income countries, and it is associated with higher maternal and neonatal complications. Thus, this study aimed to determine the trends and factors associated with them that either positively or negatively contributed to the change in teenage pregnancy in Ethiopia. Ethiopian Demographic and Health Survey data from 2005 to 2016 were used for this study. A total weighted sample of 10,655 (3265 in 2005, 4009 in 2011, and 3381 in 2016) teenagers was included. Trends and the proportion of teenage pregnancies for each factor over time were explored. Then, a logit-based multivariate decomposition analysis for a non-linear response model was fitted to identify the factors that contributed to the change in teenage pregnancy. Statistical significance was declared at p-value < 0.05 and the analysis was carried out on weighted data. Teenage pregnancy declined significantly from 16.6% (95% CI: 15.4, 17.9) to 12.5% (95% CI: 11.4, 13.6) in the study period, with an annual reduction rate of 2.5%. About 49.8% of the decrease in teenage pregnancy was attributed to the change in the effect of the characteristics. The compositional change in primary educational status (41.8%), secondary or above educational status (24.55%), being from households with a rich wealth index (1.41%) were factors positively contributed to the decline in teenage pregnancy, whereas being from a Muslim religion (−12.5%) was the factor that negatively contributed to the reduction in teenage pregnancy. This study has shown that teenage pregnancy declined significantly; however, it is still unacceptably high. The changes in compositional factors of teenagers were responsible for the observed reduction in the prevalence of teen pregnancy rates in Ethiopia. Educational status, religion, and wealth index were found to be significant factors that contributed to the reduction in teenage pregnancy. Therefore, intervention programs targeting adolescents should address the socio-economic inequalities of these influential factors to reduce teenage pregnancy and related complications.


Study population
The source population was all teenagers in five years preceding each respective survey in Ethiopia, whereas those in the selected Enumeration Areas (EAs) were the study population.The sample size was determined from the individual to recode file "IR file".A total weighted sample of 10,655 (3265 in 2005, 4009 in 2011, and 3381 in 2016) teenagers was included in this study.

Outcome variable
The outcome variable was teenage pregnancy taken as a binary response; 0 coded for "no" and 1 coded for "yes".

Independent variables
The independent variables include; educational status (no education, primary education, and secondary or above), family size (less than six, greater than or equal to six), residence (urban, rural), religion (Orthodox, Muslim, Protestant, others), occupation (employed, not employed), marital status ("unmarried" which includes never in union, separated, divorced, widowed, and "married"), husband education (no education, primary education, and secondary or above), sex of head of the household (male, female), media exposure (yes, no), wealth index (poor, middle, rich), age at first marriage, contraceptive use (using modern methods, using traditional methods, non-user-intend to use later, and do not intend to use), age at first intercourse (never had sex, active before the age of 18, and active after 18 years), and age at first birth (gave birth before 18 years, gave birth after the age of 18 years) (Table 1).

Operational definition
Teenage pregnancy Teenage pregnancy is the percentage of adolescent girls who have begun childbearing, that is the sum of the percentage who gave birth and/ or the percentage who are pregnant with their first child 22 .

Wealth index
Wealth index is a composite measure of a household's cumulative living standard divided into five quantiles using the wealth quantile data derived from the principal component analysis 22 .In this study, we recategorized into three groups as poor (includes poorer and poorest), middle, and rich (includes richer and richest).

Statistical analysis
The data were analyzed by using Stata version 16/MP software.All statistical analysis was conducted on weighted data to account for DHS complex survey design.First, a descriptive analysis was done to examine the trends with a 95% confidence interval (CI) of teenage pregnancy.Similarly, the proportion of teenage pregnancy by study participants' characteristics was explored.Then, a logit-based multivariate decomposition analysis for a nonlinear response model was implemented to determine the extent to which factors contributed to the observed change in teenage pregnancy.
Table 1.Description and measurement of independent variables.

Place of residence
The variable residence was recoded as rural and urban without any change in the dataset Age Age of the adolescent as a continuous variable

Media exposure
A composite variable obtained by combining whether the adolescent girls listen to radio, read magazine/newspaper, and watch television.It was recoded as "0" if the adolescent girls were not exposed to at least one of the three medias, and "1" if they had exposure to at least one of the three medias Educational status This is the highest educational level during interview an adolescent girl achieved and recoded into "0" for no education, "1" for primary education, and "2" for secondary or above

Marital status
Refers the current marital status of the adolescent girl and recoded into two categories as "0" for unmarried (includes never in union, separated, divorced, and widowed), and "1" for married (includes those were married and living with partner)

Sex of household head
The variable sex of household head was recoded as male and female in the dataset and used as it is

Wealth index
Wealth index was created using principal component analysis and coded as "poorest", "poorer", "middle", "richer", and "richest" in EDHS dataset.In this study, we recategorized into three groups as poor (includes poorer and poorest), middle, and rich (includes richer and richest) Age at first sex Recoded as "0" for never had sex, "1" for active before the age of 18, and "2" for active after 18 years Age at first birth Recoded as "yes" for those who gave birth before 18 years, and "no" for "no" for who gave birth after the age of 18 Age at first marriage (cohabitation) Refers the age of the adolescent girls at first marriage and used as a continuous variable

Contraceptive use and intension to use
This variable is recoded as "0" for using modern methods, "1" for using traditional methods, "2" for non-user-intend to use later, and "3" for do not intend to use Drinking water source Recoded as "1" for households who were getting drinking water from improved water sources (includes piped water sources, protected spring, protected well, and rainwater), and "0" for else Type of toilet facility Recoded as "1" for households who had improved toilet facility (includes flush to piped sewer system, flush to septic tank, flush to pit latrine, ventilated improved pit latrine, and composting toilet), and "0" for else Vol:.(1234567890)www.nature.com/scientificreports/

Scientific
In the bivariate analysis, variables with a p-value of less than 0.25 were selected for multivariate decomposition analysis.Then, a p-value of less than 0.05 with 95% CI was used to declare statistical significance after fitting to multivariate decomposition analysis in the overall decomposition.

The multivariate decomposition analysis model
Multivariate decomposition analysis for a non-linear model is used to split the difference in a distribution statistic between two groups, or its change over time, into various explanatory factors.This statistical approach uses the output from regression models to partition the components of a group difference in a statistic, such as a mean or proportion, into a component attributable to compositional differences between groups; differences in characteristics (endowments), and a component attributable to differences in the effects of characteristics (differences in coefficients).This analysis technique is equally applicable for partitioning change over time into components attributable to changing composition and changing effects [23][24][25][26] .
The dependent variable is the function of the linear combination of predictors and regression coefficients.
where Y denotes the N × 1 dependent variable vector, X is an N × K matrix of independent variables, and β is a K × 1 vector of coefficients.F (•) is any once-differentiable function mapping a linear combination of X(Xβ) to Y.The overall differences in components that reflect compositional differences between groups (endowments) and differences in the effects of characteristics (coefficients) between two groups A and B can be decomposed as: The component labeled "E" refers to the part of the differential attributable to differences in endowments or characteristics, usually called the explained component or characteristics effect.The "C" component is the difference attributable to coefficients (behavioral change) usually called the unexplained component.We have chosen group A as the comparison group and group B as the reference group.Thus, E reflects a counterfactual comparison of the difference in outcome from group A's perspective (i.e., the expected difference if group A were given group B's distribution of covariates).C reflects the counterfactual comparison of the difference in outcome from group B's perspective (i.e., the expected differences if group B were experienced in group A's behavioral response to X).
In this study, we applied a decomposition analysis to account for changes in teenage pregnancy between 2005 and 2016.The model for decomposition analysis was: 23 Where, • β0A was the intercept in the regression equation for EDHS 2016.
• β0B was the intercept in the regression equation for EDHS 2005.
• βijA was the coefficient of the jth category of the ith determinant for EDHS 2016.
• βijB was the coefficient of the jth category of the ith determinant for EDHS 2005 • XijA was the proportion of the jth category of the ith determinant for EDHS 2016.
• XijB was the proportion of the jth category of the ith determinant for EDHS 2005.

Ethical approval
Permission to access the data was obtained from the webpage of the International Review Board of Demographic and Health Survey (DHS) program.The dataset is publicly available in requesting a concept note for a proposed project from (https:// www.measu redhs.com).Initially, the Ethiopian Demographic and Health Survey (EDHS) followed its ethical procedures and the detail is also available in the full report 22 .

Socio-demographic characteristics
In this study, a total weighted sample of 10,655 adolescent teens were included.The mean ± Standard Deviation (SD) of age was almost similar with 16.9 ± 1.3 years.Regarding educational status, adolescent girls who were not educated decreased from 40% in 2005 to 13.8% in 2016.The proportion of teenagers who had media exposure increased from 42.5 to 52.4% in the same period (Table 2).

Sexual and reproductive characteristics
The mean ± SD of age at first marriage was 14.6 ± 2.2 in EDHS 2005 which raised to 15.4 ± 1.6 in EDHS 2016.About one-fourth (25.7%) of adolescent girls were sexually active before their eighteenth birth date in 2005 which later slightly decreased to 22% in 2016.Regarding knowledge of contraceptives, around 18.9% of them did not know any contraceptive methods in 2005 but decreased to 3% in 2016 (Table 2).www.nature.com/scientificreports/ of 2.5% (Fig. 1).In the first phase (2005-2011), teenage pregnancy reduced from 16.6% (95% CI: 15.4, 17.9) to 12.3% (95% CI: 11.3, 13.4) (Fig. 1).The trend of teenage pregnancy over the study period (2005-2016) varied in terms of different factors.For instance, the overall change in teenage pregnancy among rural residents was 4.6% in the study period.Based on region, the highest reduction was observed in Gambella (14.6%) percentage change followed by Beneshangulgumz (13.5%) region.The proportion of teenage pregnancy among the orthodox religion decreased from 15.8% in 2005 to 7.7% in 2016.The prevalence of teenage pregnancy was found high among adolescents who had no media exposure 22.6% as compared to 12.2% of those who had media exposure in 2005.And it decreased to 16.7% and 8.7% in 2016 respectively (Table 3).

Decomposition analysis
There has been a significant decline in the overall change in teenage pregnancy in Ethiopia from 2005 to 2016.The overall decomposition revealed that the decline in teenage pregnancy over time was explained by the difference in characteristics (endowments).However, the change due to the difference in the effect of the selected explanatory variables was not found to be significant (Table 4).
After controlling the role of change in coefficients, 49.8% of the decline in teenage pregnancy in Ethiopia was due to differences in characteristics (endowments).Thus, educational status, religion, and wealth index had a statistically significant contribution to the change in teenage pregnancy.Keeping the other variables constant, as the result of an increase in the proportion of adolescents in primary, secondary, and above school in the survey years (Table 1) had a statistically significant positive contribution to the decline of teenage pregnancy (Table 5).Followers of the Muslim religion were more likely to get married and became pregnant earlier.As a result, an increase in the proportion of Muslim followers in the survey (Table 1) had a significant negative impact on the decline in teenage pregnancy (Table 5).Regarding the wealth index, the change in the composition of the survey population from households with the rich wealth index resulted in a significant positive impact on the decrement of teenage pregnancy (Table 5).

Discussion
Despite efforts to stop early pregnancies, teenage pregnancy has been continued as a global public health problem.Therefore, this study was designed to examine the trend and pinpoint factors that contributed to the observed reduction in teenage pregnancy during the study period.The factors associated with teenage pregnancy have been the subject of previous investigations.To the best of our knowledge, there is limited evidence on the factors that contributed to the change in teenage pregnancy in Ethiopia.
The results of this study revealed that trends in teenage pregnancy prevalence decreased significantly between 2005 and 2011, even though it showed an increase between 2011 and 2016.From 2005 to 2011, the teenage pregnancy prevalence decreased by 4.3%, while it increased by 0.2% between 2011 and 2016, with an overall decrease of 4.1% from 2005 to 2016.This decline rate in the prevalence of teenage pregnancy has been consistent with Sustainable Development Goal target 3.7.2 and study findings on the trend of teenage pregnancy from 2000 to 2011 in Eastern Africa (3.5%) 27 , but higher than the study findings from West Africa (1.7%) 27 and North America www.nature.com/scientificreports/(1.2%) 28 .This could be due to the launching of the Health Extension Programme and improving access and utilization of maternal health services and decreasing the unmet need for family planning 29 .Increased political will, donor assistance, and non-governmental organization efforts to reduce early marriage in Ethiopia 30,31 may also have contributed to this decline in teenage pregnancy prevalence.Knowing the trend is important, but it's also important to understand what caused the reduction in teenage pregnancy and what factors are helping to reduce it to evaluate the current implementation strategies.The overall decomposition analysis revealed that the change in teenage pregnancy due to the difference in the effects of characteristics was not significant.Keeping coefficient changes constant, the disparity in the composition of women over time was significant and responsible for 49.8% of the decline in teenage pregnancy over the entire sample survey period (2005-2016).
Among the compositional factors, the effect of religion, educational status, and wealth index before the survey were significantly associated with the reduction in teenage pregnancy.An increase in the proportion of Muslim followers in the survey had a significant negative impact on the decline in teenage pregnancy.This finding was consistent with a study conducted in Malawi and Sri Lanka 32,33 .The possible justification might be Muslims tend www.nature.com/scientificreports/ to have an earlier marriage, and low use of family planning 34 which is leading them to become extremely young mothers.However, further study is needed to investigate the effect of religion on teenage pregnancy.An increase in the compositions of women who resides in rich households also showed a statistically significant positive contribution to the decline in teenage pregnancy.This finding was similar to a study conducted in Uganda 35 , Malawi 32 , Ethiopia 18,36 , South Sudan 37 , and sub-Saharan Africa 16,27 .A possible pathway of this influence could be that women with the lowest income tend to marry at an early age as girls' families benefit from dowries (provided by the partner's family often as cattle), while those with the highest income continue with their education and other career goals 38 .
The predominant decline in teenage pregnancy was due to the compositional change in teenagers' primary or above education attainment.An increase in the proportion of teenagers having primary school education or above in the study period had a 66.4% contribution to the decline of teenage pregnancy, similar to what had been reported in other studies in Africa 16,20,32,35,37 .Teenagers who receive an education will have a greater understanding of sexual and reproductive health, including conception and fertility.The more education a girl has, the more likely she is informed about ways of preventing early pregnancy, and the more aware she is of contraceptive options.It has been also proposed that education increases adolescent prospects for success and acts as a deterrent to early parenthood [39][40][41] .Hence, to reduce the high rate of teenage pregnancy, governmental stewardship towards making primary and secondary school more accessible in Ethiopia is strongly important.Moreover, some cultural views that impede the education of girl children should be changed.

Conclusion
Teenage pregnancy decreased significantly in the study period; however, it is still unacceptably high.The study has shown that changes in compositional factors of teenagers was responsible for the observed reduction in the prevalence of teen pregnancy rates in Ethiopia.Educational status, religion, and wealth index were found to be significant factors that contributed to the reduction in teenage pregnancy.Therefore, intervention programs targeting adolescents should address the socio-economic inequalities of these influential factors to reducing teenage pregnancy and related complications.

Figure 1 .
Figure 1.Trend of teenage pregnancy in Ethiopia by using data from EDHS 2005-2016.

Table 3 .
Trends of teenage pregnancy by selected background characteristics in Ethiopia from 2005 to 2016 EDHS in percent (%).